Time Decay of the Activity of the Reduction Reaction of NO by CO on a Pd/Al2O3 Catalyst

An experimental study is made of the time decay of activity of the CO–NO reaction on a Pd/Al₂O₃ looking at the effect on reaction order and apparent activation energy. The optimum kinetics parameters fitting the steady state data at moderate pressures are determined. The time decay curves are analyzed through various catalyst deactivation models.     

MODELISATION PRINCIPLES FOR DRYING OF GELS

When one wants to understand and model the drying of high water content gels, one needs to gather all thermal physical parameters and to derive a physical model based on independently measured parameters. We chose to work experimentally and theoretically on water diffusion and drying of spheres of polyacrylamide gel.

We have demonstrated the strong influence of vitreous transition on the relationship of water diffusivity with moisture content. Values of the diffusion coefficient and temperature shift factor for diffusion have been proposed.

Convective and micro-wave drying kinetics show the presence of a drying phase purely specific to radiation absorption. Finally, we have proposed a mathematical model containing independent physical parameters, which' not only predicts mass fluxes but also analyses critical physical phenomena.     

Information Assurance Technology Forecast 2008

A virtual roundtable (featuring panelists Steven Bellovin, Terry Benzel, Bob Blakely, Dorothy Denning, Whitfield Diffie, Jeremy Epstein, and Paulo Verissimo) discussing the next 15 years in computer security.     

Influence of pencil lead hardness on voltammetric response of graphite reinforcement carbon electrodes

This work studied the voltammetric response of graphite reinforcement electrodes made of different pencil lead hardness. The studies showed that harder graphite leads, regardless of their manufacturer, are more appropriate as electrode material for voltammetric purposes due to their higher peak currents, increasing sensitivity and reproducibility, with ΔEp closer to the theoretical value for a reversible system.     

Well-defined polymer precursors synthesized by RAFT polymerization of N,N-dimethylacrylamide/N-acryloxysuccinimide: random and block copolymers

N,N-dimethylacrylamide (DMA) and N-acryloxysuccinimide (NAS) were copolymerized by the reversible addition–fragmentation chain transfer (RAFT) polymerization technique, to obtain random and block copolymer precursors onto which different side-groups may be statistically grafted via the reactive NAS units. These reactive copolymers have interesting applications in various fields such as coatings and paints, water purification and biology. Random poly(DMA-co-NAS) copolymer chains were synthesized with a 75/25 molar ratio, high conversion, an excellent molecular weight (MW) control from 5000 to 130 000 g mol⁻¹, and low polydispersity index (M_w/M_n<1.1). Poly(DMA-b-NAS) block copolymers were synthesized by a two step method, in which a poly(DMA) homopolymer was prepared first and then used as macro-chain transfer agent to polymerize NAS. For example, a poly(DMA-b-NAS) sample was obtained with an average molecular weight of 44 300/7400 g mol⁻¹ corresponding to 447 DMA and 44 NAS units. Such block copolymers had not yet been synthesized by any controlled polymerization technique. They can be used to prepare polymers with exactly the same backbone and an increasing number of different side groups (e.g. hydrophobic, ionic or fluorescent).     

Modeling wine preferences by data mining from physicochemical properties

We propose a data mining approach to predict human wine taste preferences that is based on easily available analytical tests at the certification step. A large dataset (when compared to other studies in this domain) is considered, with white and red vinho verde samples (from Portugal). Three regression techniques were applied, under a computationally efficient procedure that performs simultaneous variable and model selection. The support vector machine achieved promising results, outperforming the multiple regression and neural network methods. Such model is useful to support the oenologist wine tasting evaluations and improve wine production. Furthermore, similar techniques can help in target marketing by modeling consumer tastes from niche markets.     

Improvement of Glycaemia and Endothelial Function by a New Low-Dose Curcuminoid in an Animal Model of Type 2 Diabetes

Curcumin has been suggested as a promising treatment for metabolic diseases, but the high doses required limit its therapeutic use. In this study, a new curcuminoid is synthesised to increase curcumin anti-inflammatory and antioxidant potential and to achieve hypoglycaemic and protective vascular effects in type 2 diabetic rats in a lower dose. In vitro, the anti-inflammatory effect was determined through the Griess reaction, and the antioxidant activity through ABTS and TBARS assays. In vivo, Goto-Kakizaki rats were treated for 2 weeks with the equimolar dose of curcumin (40 mg/kg/day) or curcuminoid (52.4 mg/kg/day). Fasting glycaemia, insulin tolerance, plasma insulin, insulin signalling, serum FFA, endothelial function and several markers of oxidative stress were evaluated. Both compounds presented a significant anti-inflammatory effect. Moreover, the curcuminoid had a marked hypoglycaemic effect, accompanied by higher GLUT4 levels in adipose tissue. Both compounds increased NO-dependent vasorelaxation, but only the curcuminoid exacerbated the response to ascorbic acid, consistent with a higher decrease in vascular oxidative and nitrosative stress. SOD1 and GLO1 levels were increased in EAT and heart, respectively. Altogether, these data suggest that the curcuminoid developed here has more pronounced effects than curcumin in low doses, improving the oxidative stress, endothelial function and glycaemic profile in type 2 diabetes.     

Generalized Hermitian Radial Basis Functions Implicits from polygonal mesh constraints

In this work we investigate a generalized interpolation approach using radial basis functions to reconstruct implicit surfaces from polygonal meshes. With this method, the user can define with great flexibility three sets of constraint interpolants: points, normals, and tangents; allowing to balance computational complexity, precision, and feature modeling. Furthermore, this flexibility makes possible to avoid untrustworthy information, such as normals estimated on triangles with bad aspect ratio. We present results of the method for applications related to the problem of modeling 2D curves from polygons and 3D surfaces from polygonal meshes. We also apply the method to problems involving subdivision surfaces and front-tracking of moving boundaries. Finally, as our technique generalizes the recently proposed HRBF Implicits technique, comparisons with this approach are also conducted.